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Full Time Machine Learning Finance Jobs (NOW HIRING)

NTENT

Machine Learning Engineer

Carlsbad, CA

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

Bracebridge Capital

Machine Learning Analyst

Boston, MA · On-site

$110K - $145K/yr

We are seeking a Machine Learning Analyst to join the growing data analytics and machine learning ... Interest in financial markets, intellectual curiosity, and comfort in working on open-ended ...

Q2

Machine Learning Engineer

Austin, TX · Hybrid

Our mission is simple: build strong and diverse communities through innovative financial technology ... SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and ...

Paylocity

Machine Learning Engineer

Schaumburg, IL · On-site

... your finances. And if it's career development you desire, we provide that, too! At Paylocity ... Machine Learning Engineer Position Overview Paylocity is growing its Machine Learning Engineering ...

Hang

Machine Learning Engineer

New York, NY · On-site +1

Hang draws from years of deep expertise in loyalty, game design, and finance with employees from ... This person will implement and develop machine learning models to enhance our platform ...

Bracebridge Capital

Machine Learning Analyst

Boston, MA · On-site

$110K - $145K/yr

We are seeking a Machine Learning Analyst to join the growing data analytics and machine learning ... Interest in financial markets, intellectual curiosity, and comfort in working on open-ended ...

Vultus Inc

Machine Learning Engineer

Honolulu, HI · On-site +1

$110K - $145K/yr

Machine Learning EngineerJob Summary We are looking for a talented Machine Learning Engineer to ... Experience 3-6 Years Employment Type Full-Time Work Location Remote / Hybrid / On-site Salary Range ...

Eccalon LLC

Machine Learning Engineer

Detroit, MI

Detroit, MI- Onsite Type: Full-time Security Clearance: No clearance required, must be clearable. The Machine Learning Engineer will be an essential member of the Research and Development Team, where ...

Q2 Software, Inc.

Machine Learning Engineer

Austin, TX · On-site

Our mission is simple: build strong and diverse communities through innovative financial technology ... SUMMARY The Machine Learning Engineer provides hands-on expertise in designing, implementing, and ...

Tapestry

Machine Learning Engineer

Mountain View, CA · On-site

About the role: We're looking for an early career Machine Learning Engineer to join our team. In ... this full-time position is $166,000 - $244,000 + bonus + equity + benefits. Within the range ...

Tapestry

Machine Learning Engineer

Mountain View, CA · On-site

About the role: We're looking for an early career Machine Learning Engineer to join our team. In ... this full-time position is $166,000 - $244,000 + bonus + equity + benefits. Within the range ...

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Full Time Machine Learning Finance information

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$25K

$92.6K

$135.5K

How much do full time machine learning finance jobs pay per year?

As of Aug 21, 2026, the average yearly pay for full time machine learning finance in the United States is $92,631.00, according to ZipRecruiter salary data. Most workers in this role earn between $75,000.00 and $109,000.00 per year, depending on experience, location, and employer.

What is a full time machine learning finance professional?

A Full Time Machine Learning Finance job involves applying machine learning techniques and algorithms to financial data and problems. Professionals in this role develop predictive models for tasks such as risk assessment, trading strategies, fraud detection, and portfolio optimization. They work closely with financial analysts and data scientists to create solutions that can automate processes, improve decision-making, and identify patterns in large datasets. The role typically requires strong knowledge of both finance and advanced machine learning methods, as well as programming and data analysis skills.

What are the key skills and qualifications needed to thrive as a full time machine learning finance professional?

To thrive as a Full Time Machine Learning Finance professional, you need a solid background in quantitative analysis, statistics, computer science, and finance, usually supported by a relevant degree. Proficiency with programming languages like Python or R, experience with machine learning frameworks (such as TensorFlow or scikit-learn), and familiarity with financial data systems are essential. Strong problem-solving abilities, attention to detail, and effective communication skills help you stand out in this field. These skills ensure the successful development and deployment of data-driven financial models that support better decision-making and risk management.

What are some common challenges faced by machine learning professionals working in the finance sector?

Machine learning professionals in finance often encounter challenges such as dealing with sensitive and highly regulated data, ensuring model transparency and explainability for compliance purposes, and adapting to rapidly changing market conditions. Additionally, integrating machine learning models with existing financial systems and collaborating closely with domain experts, such as quantitative analysts and risk managers, are key parts of the role. Staying updated on both technological advancements and regulatory changes is also essential for success in this dynamic environment.

What is the difference between Full Time Machine Learning Finance vs Full Time Data Scientist?

AspectFull Time Machine Learning FinanceFull Time Data Scientist
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of finance and machine learning certificationsDegree in Statistics, Computer Science, or related fields; data analysis and programming skills
Work EnvironmentFinancial institutions, hedge funds, banks, fintech companiesTech companies, consulting firms, finance, healthcare, retail
Industry UsageFinance-specific applications like risk modeling, algorithmic tradingBroad industry applications including marketing, healthcare, finance

Full Time Machine Learning Finance roles focus on applying machine learning techniques specifically to financial data and problems within financial institutions. In contrast, Full Time Data Scientist positions have a broader scope across various industries, utilizing data analysis and modeling skills to solve diverse business challenges. While both roles require strong technical skills, the finance-specific role emphasizes financial knowledge and applications.

Can full time machine learning finance be used in finance?

Full-time machine learning finance roles involve applying machine learning techniques to financial data for tasks such as risk assessment, trading algorithms, and fraud detection. These positions require skills in data analysis, programming, and financial modeling, and are commonly found in investment firms, banks, and fintech companies.
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The most popular types of Machine Learning Finance jobs are:

What job categories do people searching Full Time Machine Learning Finance jobs look for?

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Full Time Machine Learning Finance jobs near you
Infographic showing various Full Time Machine Learning Finance job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $92,631 per year, or $44.5 per hour.

Machine Learning Engineer

NTENT

Carlsbad, CA

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 22 days ago

Job description

Machine Learning Engineer
Position: Full time
Location: Carlsbad office
About Us:
NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search technologies directly into their business-to-consumer offerings. We are a unique group of brilliant minds intent on discovering, learning and building. We work in a vibrant atmosphere, with an emphasis on personal and professional development. This is an opportunity to tackle complex problems usually reserved for a handful of large companies in the search industry.
About the Opportunity:
We are looking for a talented Machine Learning Engineer to join our team and deliver machine learning-driven products. The right candidate will work on development, deployment, and lifecycle management of machine learning models for various large-scale applications (natural language understanding, web search and ranking, recommendation, personalization, dialog/conversation management).
Keywords:
Machine learning, natural language processing, learning-to-rank, online learning, deep learning, interactive machine learning, machine teaching, conversational agents, human computer interaction
Duties and Responsibilities:
  • Design, implement, and deploy machine learning algorithms.
  • Manage machine learning algorithm lifecycle.
  • Coordinate data collection and annotation efforts.
  • Work with real-time data and content coming from various data sources.
  • Manage machine learning data pipelines.
  • Design tests for machine learning algorithm effectiveness and performance monitoring.
  • Design tools and interfaces for interactive machine learning and teaching.
  • Research and development on cutting-edge machine learning technologies.
Qualifications and Skills:
  • Graduate degree in Computer Science with a strong background in machine learning required.
  • Strong problem-solving abilities, solid background in algorithms and data structures required.
  • Strong programming skills in Python and Scala required. Experience in other programming languages (eg. Java, R, Haskell) a plus.
  • Solid knowledge of machine learning tools (eg. scikit-learn, tensorflow, keras, pytorch, Spark MLlib) required.
  • Experience with distributed and streaming data technologies (eg. Hadoop, Spark, Kafka) required.
  • Experience with building and deploying API's with Docker and Kubernetes required.
  • Experience with natural processing tasks (eg. named entity recognition, language modeling, vector representations) required.
  • Experience with Elastic Search, Lucene a plus but not required.
  • Experience with ranking algorithms a plus but not required.
  • Experience with interactive machine learning (eg. active learning, reinforcement learning, machine teaching) a plus but not required.
The ideal candidate will be self-motivated, possess excellent communication skills (both oral and written) and be able to work independently. A keen interest in various aspects of natural language processing is essential in our multi-disciplinary team.
We offer a full comprehensive benefits package including medical, dental and vision. Employees receive a generous time off (PTO) plan and 13 holidays per year. We also offer 401(k) benefits, long term disability benefits and life.

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